Racial disparities in initiation of chemotherapy among breast cancer patients with discretionary treatment indication in the state of Georgia.

PURPOSE: The majority of breast cancer patients are diagnosed with early-stage estrogen receptor (ER) positive disease. Despite effective treatments for these cancers, Black women have higher mortality than White women. We investigated demographic and clinical factors associated with receipt of chemotherapy among those with a discretionary indication who are at risk for overtreatment. METHODS: Using Georgia Cancer Registry data, we identified females diagnosed with ER positive breast cancer who had a discretionary indication for chemotherapy (2010-2017). We used logistic regression to estimate odds ratios (ORs) and 95% confidence intervals (CIs) associating patient demographic and clinical characteristics with chemotherapy initiation overall, and comparing non-Hispanic Black (NHB) with non-Hispanic White (NHW) women within strata of patient factors. RESULTS: We identified 11,993 ER positive breast cancer patients with a discretionary indication for chemotherapy. NHB patients were more likely to initiate chemotherapy compared with NHW women (OR = 1.41, 95% CI: 1.28, 1.56). Race differences in chemotherapy initiation were pronounced among those who did not receive Oncotype DX testing (OR = 1.47, 95% CI: 1.31, 1.65) and among those residing in high socioeconomic status neighborhoods (OR = 2.48, 95% CI: 1.70, 3.61). However, we observed equitable chemotherapy receipt among patients who received Oncotype DX testing (OR = 0.90, 95% CI: 0.71, 1.14), were diagnosed with grade 1 disease (OR = 1.00, 95% CI: 0.74, 1.37), and those resided in rural areas (OR = 1.01, 95% CI: 0.76, 1.36). CONCLUSION: We observed racial disparities in the initiation of chemotherapy overall and by sociodemographic and clinical factors, and more equitable outcomes when clinical guidelines were followed.

A Comparison of Three Area-Level Indices of Neighborhood Deprivation and Socioeconomic Status and their Applicability to Breast Cancer Mortality.

Neighborhood deprivation indices are widely used in research, but the performance of these indices has rarely been directly compared in the same analysis. We examined the Area Deprivation Index, Neighborhood Deprivation Index, and Yost index, and compared their associations with breast cancer mortality. Indices were constructed for Georgia census block groups using 2011-2015 American Community Survey data. Pearson correlation coefficients and percent agreement were calculated. Associations between each index and breast cancer mortality were estimated among 36,795 women diagnosed with breast cancer using Cox proportional hazards regression. The indices were strongly correlated (absolute value of correlation coefficients > 0.77), exhibited moderate (41.4%) agreement, and were similarly associated with a 36% increase in breast cancer mortality. The similar associations with breast cancer mortality suggest the indices measure the same underlying construct, despite only moderate agreement. By understanding their correlations, agreement, and associations with health outcomes, researchers can choose the most appropriate index for analysis.

Primary care provider attitudes about and tendency to use non-recommended surveillance tests after curative breast cancer treatment.

PURPOSE: Little is known about the factors contributing to the receipt of non-recommended surveillance testing among early-stage breast cancer survivors. We assessed primary care providers (PCP) attitudes about and tendency to order non-recommended surveillance testing for asymptomatic early-stage breast cancer survivors post-adjuvant chemotherapy. METHODS: A stratified random sample of PCPs identified by early-stage breast cancer survivors were surveyed (N = 518, 61% response rate). PCPs were asked how likely they would be to order bone scans, imaging and/or tumor marker testing using a clinical vignette of an early-stage asymptomatic patient where these tests are non-recommended. A composite tendency to order score was created and categorized by tertiles (low, moderate, high). PCP-reported factors associated with high and moderate tendency to order non-recommended testing (vs. low) were estimated using multivariable, multinomial logistic regression. RESULTS: In this sample, 26% reported a high tendency to order non-recommended surveillance tests during survivorship for early-stage breast cancer survivors. PCPs who identified as family practice physicians and PCPs reporting more confidence in ordering surveillance testing were more likely to report a high tendency to order non-recommended testing (vs. low) ((aOR family practice 2.09, CI 1.2, 3.8; aOR more confidence 1.9, CI 1.1, 3.3). CONCLUSIONS: In this population-based sample of PCPs caring for breast cancer survivors, over a quarter of PCPs reported they would order non-recommended surveillance testing for asymptomatic early-stage breast cancer survivors. Efforts to better support PCPs and disseminate information about appropriate surveillance for cancer survivors are warranted.

External Validation and Comparison of a General Ward Deterioration Index Between Diversely Different Health Systems.

OBJECTIVES: Implementing a predictive analytic model in a new clinical environment is fraught with challenges. Dataset shifts such as differences in clinical practice, new data acquisition devices, or changes in the electronic health record (EHR) implementation mean that the input data seen by a model can differ significantly from the data it was trained on. Validating models at multiple institutions is therefore critical. Here, using retrospective data, we demonstrate how Predicting Intensive Care Transfers and other UnfoReseen Events (PICTURE), a deterioration index developed at a single academic medical center, generalizes to a second institution with significantly different patient population. DESIGN: PICTURE is a deterioration index designed for the general ward, which uses structured EHR data such as laboratory values and vital signs. SETTING: The general wards of two large hospitals, one an academic medical center and the other a community hospital. SUBJECTS: The model has previously been trained and validated on a cohort of 165,018 general ward encounters from a large academic medical center. Here, we apply this model to 11,083 encounters from a separate community hospital. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: The hospitals were found to have significant differences in missingness rates (> 5% difference in 9/52 features), deterioration rate (4.5% vs 2.5%), and racial makeup (20% non-White vs 49% non-White). Despite these differences, PICTURE's performance was consistent (area under the receiver operating characteristic curve [AUROC], 0.870; 95% CI, 0.861-0.878), area under the precision-recall curve (AUPRC, 0.298; 95% CI, 0.275-0.320) at the first hospital; AUROC 0.875 (0.851-0.902), AUPRC 0.339 (0.281-0.398) at the second. AUPRC was standardized to a 2.5% event rate. PICTURE also outperformed both the Epic Deterioration Index and the National Early Warning Score at both institutions. CONCLUSIONS: Important differences were observed between the two institutions, including data availability and demographic makeup. PICTURE was able to identify general ward patients at risk of deterioration at both hospitals with consistent performance (AUROC and AUPRC) and compared favorably to existing metrics.

Tailoring capture-recapture methods to estimate registry-based case counts based on error-prone diagnostic signals.

Surveillance research is of great importance for effective and efficient epidemiological monitoring of case counts and disease prevalence. Taking specific motivation from ongoing efforts to identify recurrent cases based on the Georgia Cancer Registry, we extend recently proposed "anchor stream" sampling design and estimation methodology. Our approach offers a more efficient and defensible alternative to traditional capture-recapture (CRC) methods by leveraging a relatively small random sample of participants whose recurrence status is obtained through a principled application of medical records abstraction. This sample is combined with one or more existing signaling data streams, which may yield data based on arbitrarily non-representative subsets of the full registry population. The key extension developed here accounts for the common problem of false positive or negative diagnostic signals from the existing data stream(s). In particular, we show that the design only requires documentation of positive signals in these non-anchor surveillance streams, and permits valid estimation of the true case count based on an estimable positive predictive value (PPV) parameter. We borrow ideas from the multiple imputation paradigm to provide accompanying standard errors, and develop an adapted Bayesian credible interval approach that yields favorable frequentist coverage properties. We demonstrate the benefits of the proposed methods through simulation studies, and provide a data example targeting estimation of the breast cancer recurrence case count among Metro Atlanta area patients from the Georgia Cancer Registry-based Cancer Recurrence Information and Surveillance Program (CRISP) database.

Prediction of episode of hemodynamic instability using an electrocardiogram based analytic: a retrospective cohort study.

BACKGROUND: Predicting the onset of hemodynamic instability before it occurs remains a sought-after goal in acute and critical care medicine. Technologies that allow for this may assist clinicians in preventing episodes of hemodynamic instability (EHI). We tested a novel noninvasive technology, the Analytic for Hemodynamic Instability-Predictive Indicator (AHI-PI), which analyzes a single lead of electrocardiogram (ECG) and extracts heart rate variability and morphologic waveform features to predict an EHI prior to its occurrence. METHODS: Retrospective cohort study at a quaternary care academic health system using data from hospitalized adult patients between August 2019 and April 2020 undergoing continuous ECG monitoring with intermittent noninvasive blood pressure (NIBP) or with continuous intraarterial pressure (IAP) monitoring. RESULTS: AHI-PI's low and high-risk indications were compared with the presence of EHI in the future as indicated by vital signs (heart rate > 100 beats/min with a systolic blood pressure < 90 mmHg or a mean arterial blood pressure of < 70 mmHg). 4,633 patients were analyzed (3,961 undergoing NIBP monitoring, 672 with continuous IAP monitoring). 692 patients had an EHI (380 undergoing NIBP, 312 undergoing IAP). For IAP patients, the sensitivity and specificity of AHI-PI to predict EHI was 89.7% and 78.3% with a positive and negative predictive value of 33.7% and 98.4% respectively. For NIBP patients, AHI-PI had a sensitivity and specificity of 86.3% and 80.5% with a positive and negative predictive value of 11.7% and 99.5% respectively. Both groups performed with an AUC of 0.87. AHI-PI predicted EHI in both groups with a median lead time of 1.1 h (average lead time of 3.7 h for IAP group, 2.9 h for NIBP group). CONCLUSIONS: AHI-PI predicted EHIs with high sensitivity and specificity and within clinically significant time windows that may allow for intervention. Performance was similar in patients undergoing NIBP and IAP monitoring.

Germline Genetic Testing After Cancer Diagnosis.

Importance: Germline genetic testing is recommended by practice guidelines for patients diagnosed with cancer to enable genetically targeted treatment and identify relatives who may benefit from personalized cancer screening and prevention. Objective: To describe the prevalence of germline genetic testing among patients diagnosed with cancer in California and Georgia between 2013 and 2019. Design, Setting, and Participants: Observational study including patients aged 20 years or older who had been diagnosed with any type of cancer between January 1, 2013, and March 31, 2019, that was reported to statewide Surveillance, Epidemiology, and End Results registries in California and Georgia. These patients were linked to genetic testing results from 4 laboratories that performed most germline testing for California and Georgia. Main Outcomes and Measures: The primary outcome was germline genetic testing within 2 years of a cancer diagnosis. Testing trends were analyzed with logistic regression modeling. The results of sequencing each gene, including variants associated with increased cancer risk (pathogenic results) and variants whose cancer risk association was unknown (uncertain results), were evaluated. The genes were categorized according to their primary cancer association, including breast or ovarian, gastrointestinal, and other, and whether practice guidelines recommended germline testing. Results: Among 1 369 602 patients diagnosed with cancer between 2013 and 2019 in California and Georgia, 93 052 (6.8%) underwent germline testing through March 31, 2021. The proportion of patients tested varied by cancer type: male breast (50%), ovarian (38.6%), female breast (26%), multiple (7.5%), endometrial (6.4%), pancreatic (5.6%), colorectal (5.6%), prostate (1.1%), and lung (0.3%). In a logistic regression model, compared with the 31% (95% CI, 30%-31%) of non-Hispanic White patients with male breast cancer, female breast cancer, or ovarian cancer who underwent testing, patients of other races and ethnicities underwent testing less often: 22% (95% CI, 21%-22%) of Asian patients, 25% (95% CI, 24%-25%) of Black patients, and 23% (95% CI, 23%-23%) of Hispanic patients (P < .001 using the χ2 test). Of all pathogenic results, 67.5% to 94.9% of variants were identified in genes for which practice guidelines recommend testing and 68.3% to 83.8% of variants were identified in genes associated with the diagnosed cancer type. Conclusions and Relevance: Among patients diagnosed with cancer in California and Georgia between 2013 and 2019, only 6.8% underwent germline genetic testing. Compared with non-Hispanic White patients, rates of testing were lower among Asian, Black, and Hispanic patients.

Drivers of racial, regional, and socioeconomic disparities in late-stage breast cancer mortality.

BACKGROUND: The authors identified tumor, treatment, and patient characteristics that may contribute to differences in breast cancer (BC) mortality by race, rurality, and area-level socioeconomic status (SES) among women diagnosed with stage IIIB-IV BC in Georgia. METHODS: Using the Georgia Cancer Registry, 3084 patients with stage IIIB-IV primary BC (2013-2017) were identified. Cox proportional hazards regression was used to calculate the hazard ratios (HRs) and 95% confidence intervals (CIs) comparing mortality among non-Hispanic Black (NHB) versus non-Hispanic White (NHW), residents of rural versus urban neighborhoods, and residents of low- versus high-SES neighborhoods by tumor, treatment, and patient characteristics. The mediating effects of specific characteristics on the association between race and BC mortality were estimated. RESULTS: Among the study population, 41% were NHB, 21% resided in rural counties, and 72% resided in low SES neighborhoods. The authors observed mortality disparities by race (HR, 1.27; 95% CI, 1.13, 1.41) and rurality (HR, 1.14; 95% CI, 1.00, 1.30), but not by SES (HR, 1.04; 95% CI, 0.91, 1.19). In the stratified analyses, racial disparities were the most pronounced among women with HER2 overexpressing tumors (HR, 2.30; 95% CI, 1.53, 3.45). Residing in a rural county was associated with increased mortality among uninsured women (HR, 2.25; 95% CI, 1.31, 3.86), and the most pronounced SES disparities were among younger women (<40 years: HR, 1.46; 95% CI, 0.88, 2.42). CONCLUSIONS: There is considerable variation in racial, regional, and socioeconomic disparities in late-stage BC mortality by tumor, treatment, and patient characteristics.

Perceived financial decline related to breast reconstruction following mastectomy in a diverse population-based cohort.

BACKGROUND: Despite mandated insurance coverage for breast reconstruction following mastectomy, health care costs are increasingly passed on to women through cost-sharing arrangements and high-deductible health plans. In this population-based study, the authors assessed perceived financial and employment declines related to breast reconstruction following mastectomy. METHODS: Women with early-stage breast cancer (stages 0-II) diagnosed between July 2013 and May 2015 who underwent mastectomy were identified through the Surveillance, Epidemiology, and End Results registries of Georgia and Los Angeles and were surveyed. Primary outcome measures included patients' appraisal of their financial and employment status after cancer treatment. Multivariable models evaluated the association between breast reconstruction and primary outcomes. RESULTS: Among 883 patients with breast cancer who underwent mastectomy, 44.2% did not undergo breast reconstruction, and 55.8% underwent reconstruction. Overall, 21.9% of the cohort reported being worse off financially since their diagnosis (25.8% with reconstruction vs 16.6% without reconstruction; P = .002). Women who underwent reconstruction reported higher out-of-pocket medical expenses (32.1% vs 15.6% with expenses greater than $5000; P < .001). Reconstruction was independently associated with a perceived decline in financial status (odds ratio, 1.92; 95% confidence interval, 1.15-3.22; P = .013). Among women who were employed at the time of their diagnosis, there was no association between reconstruction and a perceived decline in employment status (P = .927). CONCLUSIONS: In this diverse cohort of women who underwent mastectomy, those who elected to undergo reconstruction experienced higher out-of-pocket medical expenses and self-reported financial decline. Patients, providers, and policymakers should be aware of the potential financial implications related to reconstruction despite mandatory insurance coverage.

Barriers to the Use of Active Surveillance for Thyroid Cancer Results of a Physician Survey.

OBJECTIVE: The aim of this study was to determine physician-reported use of and barriers to active surveillance for thyroid cancer. SUMMARY BACKGROUND DATA: It is not clear whether active surveillance for thyroid cancer is widely used. METHODS: Surgeons and endocrinologists identified by thyroid cancer patients from the Surveillance, Epidemiology, and End Results (SEER) registries of Georgia and Los Angeles County were surveyed between 2018 and 2019. Multivariable weighted logistic regression analyses were conducted to determine physician acceptance and use of active surveillance. Results: Of the 654 eligible physicians identified, 448 responded to the survey (69% response rate). The majority (76%) believed that active surveillance was an appropriate management option, but only 44% used it in their practice. Characteristics of physicians who stated that active surveillance was appropriate management, but did not report using it included more years in practice (reference group <10 years in practice): 10 to 19 years [odds ratio, OR 0.50 [95% confidence interval, CI 0.28-0.92]; 20 to 29 years [OR 0.31 (95% CI 0.15-0.62)]; >30 years [OR 0.30 (95% CI 0.15-0.61)] and higher patient volume 11 to 30 patients per year [OR 0.39 (95% CI 0.21 -0.70)] and >50 patients per year [OR 0.33 (95% CI 0.16-0.71)] compared to < 10, with no significant difference in those seeing 31 to 50 patients. Physicians reported multiple barriers to implementing active surveillance including patient does not want (80.3%), loss to follow-up concern (78.4%), more patient worry (57.6%), and malpractice lawsuit concern (50.9%). CONCLUSION AND RELEVANCE: Despite most physicians considering active surveillance to be appropriate management, more than half are not using it. Addressing existing barriers is key to improving uptake.

Time to Surgical Treatment and Facility Characteristics as Potential Drivers of Racial Disparities in Breast Cancer Mortality.

BACKGROUND: Black women are more likely to die of breast cancer than White women. This study evaluated the contribution of time to primary surgical management and surgical facility characteristics to racial disparities in breast cancer mortality among both Black and White women. METHODS: The study identified 2224 Black and 3787 White women with a diagnosis with stages I to III breast cancer (2010-2014). Outcomes included time to surgical treatment (> 30 days from diagnosis) and breast cancer mortality. Odds ratios (ORs) and 95% confidence intervals (CIs) associating surgical facility characteristics with surgical delay were computed, and Cox proportional hazards regression was used to compute hazard ratios (HRs) and 95% CIs associating delay and facility characteristics with breast cancer mortality. RESULTS: Black women were two times more likely to have a surgical delay (OR, 2.15; 95% CI, 1.92-2.41) than White women. Racial disparity in surgical delay was least pronounced among women treated at a non-profit facility (OR, 1.95; 95% CI, 1.70-2.25). The estimated mortality rate for Black women was two times that for White women (HR, 2.00; 95% CI, 1.83-2.46). Racial disparities in breast cancer mortality were least pronounced among women who experienced no surgical delay (HR, 1.81; 95% CI, 1.28-2.56), received surgery at a government facility (HR, 1.31; 95% CI, 0.76-2.27), or underwent treatment at a Commission on Cancer-accredited facility (HR, 1.82; 95% CI, 1.38-2.40). CONCLUSIONS: Black women were more likely to experience a surgical delay and breast cancer death. Persistent racial disparities in breast cancer mortality were observed across facility characteristics except for government facilities.

A dyadic survey study of partner engagement in and patient receipt of guideline-recommended colorectal cancer surveillance.

BACKGROUND: We investigated whether partner (spouse or intimate partner) engagement in colorectal cancer (CRC) surveillance is associated with patient receipt of surveillance. METHODS: From 2019 to 2020 we surveyed Stage III CRC survivors diagnosed 2014-2018 at an academic cancer center, a community oncology practice and the Georgia SEER registry, and their partners. Partner engagement was measured across 3 domains: Informed about; Involved in; and Aware of patient preferences around surveillance. We evaluated bivariate associations between domains of partner engagement and independent partner variables. Analysis of variance and multivariable logistic regression were used to compare domains of engagement with patient-reported receipt of surveillance. RESULTS: 501 patients responded (51% response rate); 428 had partners. 311 partners responded (73% response rate). Partners were engaged across all domains. Engagement varied by sociodemographics. Greater partner involvement was associated with decreased odds of receipt of composite surveillance (OR 0.67, 95% CI 0.48-0.93) and trended towards significance for decreased odds of receipt of endoscopy (OR 0.60, 95% CI 0.34-1.03) and CEA (OR 0.75, 95% CI 0.55-1.04). Greater partner awareness was associated with increased odds of patients' receipt of endoscopy (OR 2.18, 95% CI 1.15-4.12) and trended towards significance for increased odds of receipt of composite surveillance (OR 1.30, 95% CI 0.91-2.04). CONCLUSION: Partners are engaged (informed, involved, and aware) in CRC surveillance. Future research to develop dyadic interventions that capitalize on the positive aspects of partner engagement may help partners effectively engage in surveillance to improve patient care.

Prediction of Postoperative Deterioration in Cardiac Surgery Patients Using Electronic Health Record and Physiologic Waveform Data.

BACKGROUND: Postoperative hemodynamic deterioration among cardiac surgical patients can indicate or lead to adverse outcomes. Whereas prediction models for such events using electronic health records or physiologic waveform data are previously described, their combined value remains incompletely defined. The authors hypothesized that models incorporating electronic health record and processed waveform signal data (electrocardiogram lead II, pulse plethysmography, arterial catheter tracing) would yield improved performance versus either modality alone. METHODS: Intensive care unit data were reviewed after elective adult cardiac surgical procedures at an academic center between 2013 and 2020. Model features included electronic health record features and physiologic waveforms. Tensor decomposition was used for waveform feature reduction. Machine learning-based prediction models included a 2013 to 2017 training set and a 2017 to 2020 temporal holdout test set. The primary outcome was a postoperative deterioration event, defined as a composite of low cardiac index of less than 2.0 ml min-1 m-2, mean arterial pressure of less than 55 mmHg sustained for 120 min or longer, new or escalated inotrope/vasopressor infusion, epinephrine bolus of 1 mg or more, or intensive care unit mortality. Prediction models analyzed data 8 h before events. RESULTS: Among 1,555 cases, 185 (12%) experienced 276 deterioration events, most commonly including low cardiac index (7.0% of patients), new inotrope (1.9%), and sustained hypotension (1.4%). The best performing model on the 2013 to 2017 training set yielded a C-statistic of 0.803 (95% CI, 0.799 to 0.807), although performance was substantially lower in the 2017 to 2020 test set (0.709, 0.705 to 0.712). Test set performance of the combined model was greater than corresponding models limited to solely electronic health record features (0.641; 95% CI, 0.637 to 0.646) or waveform features (0.697; 95% CI, 0.693 to 0.701). CONCLUSIONS: Clinical deterioration prediction models combining electronic health record data and waveform data were superior to either modality alone, and performance of combined models was primarily driven by waveform data. Decreased performance of prediction models during temporal validation may be explained by data set shift, a core challenge of healthcare prediction modeling.

Healthcare Access Dimensions and Guideline-Concordant Ovarian Cancer Treatment: SEER-Medicare Analysis of the ORCHiD Study.

BACKGROUND: Racial disparities exist in receipt of guideline-concordant treatment of ovarian cancer (OC). However, few studies have evaluated how various dimensions of healthcare access (HCA) contribute to these disparities. METHODS: We analyzed data from non-Hispanic (NH)-Black, Hispanic, and NH-White patients with OC diagnosed in 2008 to 2015 from the SEER-Medicare database and defined HCA dimensions as affordability, availability, and accessibility, measured as aggregate scores created with factor analysis. Receipt of guideline-concordant OC surgery and chemotherapy was defined based on the NCCN Guidelines for Ovarian Cancer. Multivariable-adjusted modified Poisson regression models were used to assess the relative risk (RR) for guideline-concordant treatment in relation to HCA. RESULTS: The study cohort included 5,632 patients: 6% NH-Black, 6% Hispanic, and 88% NH-White. Only 23.8% of NH-White patients received guideline-concordant surgery and the full cycles of chemotherapy versus 14.2% of NH-Black patients. Higher affordability (RR, 1.05; 95% CI, 1.01-1.08) and availability (RR, 1.06; 95% CI, 1.02-1.10) were associated with receipt of guideline-concordant surgery, whereas higher affordability was associated with initiation of systemic therapy (hazard ratio, 1.09; 95% CI, 1.05-1.13). After adjusting for all 3 HCA scores and demographic and clinical characteristics, NH-Black patients remained less likely than NH-White patients to initiate systemic therapy (hazard ratio, 0.86; 95% CI, 0.75-0.99). CONCLUSIONS: Multiple HCA dimensions predict receipt of guideline-concordant treatment but do not fully explain racial disparities among patients with OC. Acceptability and accommodation are 2 additional HCA dimensions which may be critical to addressing these disparities.

Tracking Peripheral Artery Motion and Vascular Resistance With a Multimodal Wearable Sensor Under Pressure Perturbations.

The status of peripheral arteries is known to be a key physiological indicator of the body's response to both acute and chronic medical conditions. In this paper, peripheral artery deformation is tracked by wearable photoplethysmograph (PPG) and piezo-electric (polyvinylidene difluoride, PVDF) sensors, under pressure-varying cuff. A simple mechanical model for the local artery and intervening tissue captures broad features present in the PPG and PVDF signals on multiple swine subjects, with respect to varying cuff pressure. These behaviors provide insight into the robustness of cardiovascular property identification by noninvasive wearable sensing. This is found to help refine noninvasive blood pressure measurements and estimation of systemic vascular resistance (SVR) using selected features of sensor amplitude versus applied pressure.

Trans-Ocular Brain Impedance Indices Predict Pressure Reactivity Index Changes in a Porcine Model of Hypotension and Cerebral Autoregulation Perturbation.

BACKGROUND: Cerebrovascular autoregulation (CA) is a protective mechanism that enables the cerebral vasculature to automodulate tone in response to changes in cerebral perfusion pressure to ensure constant levels of cerebral blood flow (CBF) and oxygen delivery. CA can be impaired after neurological injury and contributes to secondary brain injury. In this study, we report novel impedance indices using trans-ocular brain impedance (TOBI) during controlled systemic hemorrhage and hypotension to assess CA in comparison with pressure reactivity index (PRx). METHODS: Yorkshire swine were instrumented to record intracranial pressure (ICP), mean arterial pressure (MAP), and CBF. TOBI was recorded using electrocardiographic electrodes placed on the closed eyelids. Impedance changes (dz) were recorded in response to introducing an alternating current (0.4 mA) through the electrodes. MAP, ICP, and CBF were also measured. Animals were subjected to a controlled hemorrhage to remove 30-40% of each animal's total blood volume over 25-35 min. Hemorrhage was titrated to reach an MAP of approximately 35 mm Hg and end-tidal carbon dioxide above 28 mm Hg. PRx was calculated as a moving Pearson correlation between MAP and ICP. TOBI indices were calculated as the amplitude of the respiratory-induced changes in dz. DZx was calculated as a moving Pearson correlation between dz and MAP. TOBI indices (dz and DZx) were compared with hemodynamic indicators and PRx. RESULTS: dz was shown to be highly correlated with MAP, ICP, cerebral perfusion pressure, and CBF (r = - 0.823, - 0.723, - 0.813, and - 0.726), respectively (p < 0.0001). During hemorrhage, cerebral perfusion pressure and CBF had a mean percent decrease (standard deviation) from baseline of - 54.2% (12.5%) and - 28.3% (14.7%), respectively, whereas dz increased by 277% (268%). Receiver operator characteristics and precision-recall curves demonstrated high predictive performance of DZx when compared with PRx with an area under the curve above 0.82 and 0.89 for receiver operator characteristic and precision-recall curves, respectively, with high sensitivity and positive predictive power. CONCLUSIONS: TOBI indices appear to track changes in PRx and hemodynamics that affect CA during hemorrhage-induced hypotension. TOBI may offer a suitable, less invasive surrogate to PRx for monitoring and assessing CA.

An interpretable neural network for outcome prediction in traumatic brain injury.

BACKGROUND: Traumatic Brain Injury (TBI) is a common condition with potentially severe long-term complications, the prediction of which remains challenging. Machine learning (ML) methods have been used previously to help physicians predict long-term outcomes of TBI so that appropriate treatment plans can be adopted. However, many ML techniques are "black box": it is difficult for humans to understand the decisions made by the model, with post-hoc explanations only identifying isolated relevant factors rather than combinations of factors. Moreover, such models often rely on many variables, some of which might not be available at the time of hospitalization. METHODS: In this study, we apply an interpretable neural network model based on tropical geometry to predict unfavorable outcomes at six months from hospitalization in TBI patients, based on information available at the time of admission. RESULTS: The proposed method is compared to established machine learning methods-XGBoost, Random Forest, and SVM-achieving comparable performance in terms of area under the receiver operating characteristic curve (AUC)-0.799 for the proposed method vs. 0.810 for the best black box model. Moreover, the proposed method allows for the extraction of simple, human-understandable rules that explain the model's predictions and can be used as general guidelines by clinicians to inform treatment decisions. CONCLUSIONS: The classification results for the proposed model are comparable with those of traditional ML methods. However, our model is interpretable, and it allows the extraction of intelligible rules. These rules can be used to determine relevant factors in assessing TBI outcomes and can be used in situations when not all necessary factors are known to inform the full model's decision.

Endogenous Endophthalmitis Caused by ST66-K2 Hypervirulent Klebsiella pneumoniae, United States.

We describe a case of endogenous endophthalmitis caused by sequence type 66-K2 hypervirulent Klebsiella pneumoniae in a diabetic patient with no travel history outside the United States. Genomic analysis showed the pathogen has remained highly conserved, retaining >98% genetic similarity to the original strain described in Indonesia in 1935.

Genomic Characterizations of Clade III Lineage of Candida auris, California, USA.

Candida auris is an emerging multidrug-resistant yeast. We describe an ongoing C. auris outbreak that began in October 2019 in Los Angeles, California, USA. We used genomic analysis to determine that isolates from 5 of 6 patients belonged to clade III; 4 isolates were closely related.

Health-related quality of life among colorectal cancer survivors of diverse sexual orientations.

BACKGROUND: The purpose of this study was to examine the health-related quality of life of sexual minority survivors in comparison with heterosexual survivors. METHODS: Four hundred eighty eligible survivors participated in a telephone survey that measured survivors' outcomes, which consisted of physical and mental quality of life and self-rated fair or poor health. These survivors were diagnosed with stage I, II, or III colorectal cancer an average of 3 years before the survey and were recruited from 4 cancer registries. Using forward selection with generalized linear models or logistic regression models, the authors considered 4 domains-personal factors, environmental factors, health condition characteristics, and body function and structure-as correlates for each survivorship outcome. RESULTS: The authors found that unadjusted physical quality of life and self-rated fair/poor health were similar for all survivors. Sexual minority survivors had poorer unadjusted mental quality of life in comparison with heterosexual survivors. After adjustments for covariates, this difference was no longer statistically significant. Three domains (personal factors, health condition characteristics, and body function and structure) explained colorectal cancer survivors' fair/poor health and 46% of the variance in physical quality of life, whereas 56% of the variance in mental quality of life was explained by personal factors, body function and structure, and environmental factors. CONCLUSIONS: This study has identified modifiable factors that can be used to improve cancer survivors' quality of life and are, therefore, relevant to ongoing efforts to improve the survivorship experience.